title: Disease liability prediction from large scale genotyping data using classifiers with a reject option.
abstract: Genome-wide association studies (GWA) try to identify the genetic polymorphisms associated with variation in phenotypes. However, the most significant genetic variants may have a small predictive power to forecast the future development of common diseases. We study the prediction of the risk of developing a disease given genome-wide genotypic data using classifiers with a reject option, which only make a prediction when they are sufficiently certain, but in doubtful situations may reject making a classification. To test the reliability of our proposal, we used the Wellcome Trust Case Control Consortium (WTCCC) data set, comprising 14,000 cases of seven common human diseases and 3,000 shared controls.
authors.affiliation: Oviedo University, Gijón.
authors.forename: José R
authors.initials: JR
authors.lastname: Quevedo
authors.forename: Antonio
authors.initials: A
authors.lastname: Bahamonde
authors.forename: Miguel
authors.initials: M
authors.lastname: Pérez-Enciso
authors.forename: Oscar
authors.initials: O
authors.lastname: Luaces
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide